Résumé: Data warehouses are based on multidimensional modeling. Using On-Line Analytical
Processing (OLAP) tools, decision makers navigate through and analyze multidimensional
data. Typically, users need to analyze data at different aggregation levels (using roll-up and
drill-down functions). Therefore, aggregation knowledge should be adequately represented in
conceptual multidimensional models, and mapped in subsequent logical and physical models.
However, current conceptual multidimensional models poorly represent aggregation knowledge,
which (1) has a complex structure and dynamics and (2) is highly contextual. In order to
account for the characteristics of this knowledge, we propose to represent it with objects (UML
class diagrams) and rules in the Production Rule Representation language (PRR). Static
aggregation knowledge is represented in the class diagrams, while rules represent the
dynamics (i.e. how aggregation may be performed depending on context). We present the class
diagrams, and a typology and examples of associated rules. We argue that this representation of
aggregation knowledge enables an early modeling of user requirements in a data warehouse
project. A prototype has been developed based on the Java Expert System Shell (Jess).